Digital images include a plurality of pixels arranged in rows and columns. For example, each individual pixel may be associated with a sensor, such as an infrared sensor (e.g., a microbolometer), a visible spectrum sensor, and/or other appropriate sensing element.
Failures and/or defects in such sensors or other components of an imaging device may result in one or more individual pixels or groups of pixels exhibiting anomalous behavior (e.g., “bad pixels”). Anomalous pixels can be especially problematic for imaging devices with small array sizes (e.g., having correspondingly small numbers of pixels), as each pixel may have a proportionally larger contribution to the overall image than in large array sizes.
Conventional quality control techniques typically include human and/or machine-based evaluation of captured images to identify anomalous pixels before imaging devices are shipped from the factory. However, conventional techniques may not always identify anomalous pixels reliably, especially in the case of intermittent operation. In addition, human-based evaluation may not be practical or cost effective for large volume manufacturing.